Evidence map›Paper›PMID 34289044›Full record

ArticleSystematic biology2022

Improving Phylogenies Based on Average Nucleotide Identity, Incorporating Saturation Correction and Nonparametric Bootstrap Support.

Sean Gosselin, Matthew S Fullmer, Yutian Feng, Johann Peter Gogarten

Abstract read
In one paragraph

Article in Systematic biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

27 citing papers in PubMed.

  1. Article
  2. Article
  3. Genomic and Functional Characterization ofFrontiers in microbiology · 2026
    Article
  4. Microbial Evolution and Systematics: Archaea and Bacteria.Progress in molecular and subcellular biology · 2026
    Review
  5. Genomic-enabled classification of threeJournal of clinical microbiology · 2025
    Article
  6. Article
  7. Article
  8. EvANI benchmarking workflow for evolutionary distance estimation.bioRxiv : the preprint server for biology · 2025
    Article
  9. Article
  10. Genomic Analysis of 96Viruses · 2025
    Article
  11. Article
  12. Article
  13. The unique and enigmatic spirochete symbiont of latrunculid sponges.bioRxiv : the preprint server for biology · 2024
    Article
  14. Article
  15. The Metabolism ofMicroorganisms · 2024
    Article
  16. Article
  17. Article
  18. Article
  19. Update on the proposed minimal standards for the use of genome data for the taxonomy of prokaryotes.International journal of systematic and evolutionary microbiology · 2024
    Article
  20. Comparative Analyses of Bacteriophage Genomes.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sean GosselinDepartment of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06268-3125, USA.
Matthew S FullmerDepartment of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06268-3125, USA.
Yutian FengDepartment of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06268-3125, USA.
Johann Peter GogartenDepartment of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06268-3125, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Whole-genome comparisons based on average nucleotide identities (ANI) and the genome-to-genome distance calculator have risen to prominence in rapidly classifying prokaryotic taxa using whole-genome sequences. Some implementations have even been proposed as a new standard in species classification and have become a common technique for papers describing newly sequenced genomes. However, attempts to apply whole-genome divergence data to the delineation of higher taxonomic units and to phylogenetic inference have had difficulty matching those produced by more complex phylogenetic methods. We present a novel method for generating statistically supported phylogenies of archaeal and bacterial groups using a combined ANI and alignment fraction-based metric. For the test cases to which we applied the developed approach, we obtained results comparable with other methodologies up to at least the family level. The developed method uses nonparametric bootstrapping to gauge support for inferred groups. This method offers the opportunity to make use of whole-genome comparison data, that is already being generated, to quickly produce phylogenies including support for inferred groups. Additionally, the developed ANI methodology can assist the classification of higher taxonomic groups.[Average nucleotide identity (ANI); genome evolution; prokaryotic species delineation; taxonomy.].

Indexed as

Genome, BacterialNucleotidesPhylogenyProkaryotic CellsSequence Analysis, DNANucleotides

Identifiers

PMID34289044
PMCPMC8830074

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.